Perceived Value of Cloud Based Information Systems.
Case: Accounting Information Systems.
Information Systems Science Master's thesis
Anna Zhygalova 2013
Aalto University, P.O. BOX 11000, 00076 AALTO www.aalto.fi Abstract of master’s thesis
Author Anna Zhygalova
Title of thesis Perceived Value of Cloud Based Information Systems. Case: Accounting Information Systems
Degree Information and Service Management Thesis advisor(s) Esko Penttinen, Aleksandre Asatiani
Year of approval 2013 Number of pages 114 Language English
Cloud based information systems are considered to benefit the organizations through their superior information capabilities compared to traditional information systems. Strong adoption of the cloud computing in the recent years has also affected the view on outsourcing of information technology enabled processes and led to creation of new service offerings represented by a combination of cloud and outsourcing. Earlier research closely considers the benefits of cloud computing and business process outsourcing. However, the empirical evidence of the positive relationship between the use of the cloud and outsourcing and organizational performance is lacking. The focus of the current research is to fill in this gap and analyze managerial perceptions of the value of cloud based information systems by grouping organizations based on their outsourcing pattern: 1) non-outsourcing, 2) selective outsourcing and 3) total outsourcing. Results of the analysis revealed the higher perceived improvements for cloud users compared to non-cloud users for organizations that perform processes in-house and practice selective outsourcing. For organizations, which are inclined towards total outsourcing, the use of cloud does not lead to significantly higher improvements. The clusters with low number of cloud users and outsourcing perceived most improvements in basic accuracy and data quality, while the clusters with high number of cloud users perceived highest improvements in accessibility. Based on the findings six propositions are identified and suggested for further research.
Keywords
LIST OF FIGURES
Figure 1. A process oriented model of IT business value (Mooney et al., 1996) ... 9
Figure 2. How IT creates business value: process theory (Soh & Markus, 1994) ... 10
Figure 3. Resource-based view of IT business value (Melville et al., 2004) ... 12
Figure 4. IT and economic performance framework (Dedrick et al., 2003) ... 13
Figure 5. Synthesis IS business value model (Schryen, 2012) ... 15
Figure 6. Organizational operational environment and perceived operational performance and IT value (Ragowsky et al., 2000) ... 18
Figure 7. Information system success model (DeLone & McLean, 1992) ... 19
Figure 8. Dimensions of IT business value (Mooney et al., 1996) ... 22
Figure 9. Cloud computing stack (Bhardwaj et al., 2010) ... 26
Figure 10. Cloud computing ontology (Youseff et al., 2008) ... 26
Figure 11. Illustration of cloud computing models (Géczy, Izumi, & Hasida, 2012) ... 29
Figure 12. Cloud computing benefits (Carroll et al., 2011) ... 32
Figure 13. Reasons to consider SaaS (Koehler & Anandasivam, 2010) ... 34
Figure 14. Cloud computing risks (Carroll et al., 2011) ... 37
Figure 15. Accounting process (Everaert et al., 2008) ... 44
Figure 16. Literature review synthesis: conceptual analysis model ... 48
Figure 17. Outsourcing pattern for cluster #1 ... 58
Figure 18. Outsourcing pattern for cluster #2 ... 59
Figure 19. Outsourcing rate for cluster #3 ... 60
Figure 20. Outsourcing rate for cluster #4 ... 61
LIST OF TABLES Table 1. IT capabilities and their organizational impacts (Davenport & Short, 1990) ... 23
Table 2. Cloud computing service models ... 27
Table 3. Cloud computing deployment models (Brian et al., 2008; Hoberg, Wollersheim, & Krcmar, 2012) ... 28
Table 4. Accounting processes being evaluated in the survey ... 50
GLOSSARY
ANOVA Analysis of Variance
API Application Programming Interface
BPO Business Process Outsourcing
CaaS Communication as a Service
DaaS Data storage as a Service
HaaS Hardware as a Service
HTTP Hypertext Transfer Protocol
IaaS Infrastructure as a Service
IS Information System
IT Information Technology
SaaS Software as a Service
SLA Service Level Agreement
PaaS Platform as a Service
RBV Resource Based View
R&D Research and Development
ROA Return on Assets
TCE Transaction Cost Economics
TABLE OF CONTENTS
1 Introduction 1
1.1 Background and motivation 1
1.2 Objectives of the study 2
2 Literature review 4
2.1 Business value of information systems 4
2.1.1 Concepts and approaches 4
2.1.2 Perceptual view 16
2.1.3 Value through IT capabilities 21
2.2 Cloud based information systems 24
2.2.1 Concept overview 24
2.2.2 Benefits of cloud computing 29
2.2.3 Risks of cloud computing 35
2.3 Cloud computing and business process outsourcing 38
2.3.1 Overview of business process outsourcing 38
2.3.2 Benefits of business process outsourcing 41
2.3.3 Risks of business process outsourcing 42
2.3.4 Outsourcing of accounting processes 44
2.3.5 Outsourcing to the cloud 45
2.4 Literature review synthesis: conceptual framework 47
3 Methodology 50
3.1 Outsourcing survey 50
3.2 Focus group 51
3.3 Data analysis software and methods 52
4 Analysis and interpretation of results 58
4.1 Profiling of the clusters 58
4.2 General findings and propositions for further research 70
4.3 Limitations of the research 72
5 Conclusions 74
5.3 Managerial conclusions 75
6 References 78
7 Appendices 83
7.1 Appendix A. Cluster analysis: general tables 83
7.2 Appendix B. Cluster analysis: Cluster #1 102
7.3 Appendix C: Cluster analysis: Cluster #2 104
7.4 Appendix D: Cluster analysis: Cluster #3 106
1
Introduction
1.1 Background and motivation
Adoption of the cloud computing services has been rapidly growing during the past years. Gartner estimated public cloud services at $129 billion for 2013 with a five-year compound annual growth rate (CAGR) of 17% (Potter, 2013). The use of cloud computing promises organizations significant improvements in their business processes due to superior capabilities of the cloud based information systems compared to traditional information systems. Superior capabilities of the cloud computing, as stated by numerous research findings, lead to improvements in accessibility of the data, information processing and data analysis, tracking of the end-users and their data manipulations, and improving automation of the business processes enabled through the use of the information technology (IT-enabled business processes).
Emergence and increasing adoption of the cloud has also strongly affected the views on outsourcing of the business processes. Organizations no longer perceive outsourcing as transferring their internal business processes or software to be performed or maintained by the external party. Now organizations purchase actual services from the outsourcing service providers, which are often delivered through the cloud (Pring, 2010). Thus, the concepts of the business process outsourcing and cloud computing are merging to create the new service offering, where cloud opens new possibilities for organizations to benefit from professionalism of the external service providers while at the same time maintaining full control over performance and quality of the processes being outsourced.
Exploring and understanding the business value of the business process outsourcing to the cloud arises as an important milestone in leveraging cloud computing and outsourcing to enhance performance of the organizations. However, despite of the relatively high number of the research papers dedicated towards outlining the benefits of the cloud based information systems, literature has a limited number of quantitative analysis that aims at identification of the relationship between the performance of the organizations and the use of the cloud based information systems and outsourcing.
Current research aims at filling in this gap by analyzing organizations based on their outsourcing patterns and linking the use of the cloud based information systems and outsourcing to the improvements in the business processes.
1.2 Objectives of the study
Four main objectives can be identified for the current research. The first objective is conducting a background research regarding the business value of the information systems (IS), cloud computing and business process outsourcing in order to lay the basis for the empirical part of the research. The background research in the area of IS value is dedicated towards exploration of the most widely used approaches towards identification of the value investments in information technology and information systems as well as defining and explaining the capabilities of the information systems through which information system value is realized.
Cloud computing section of the background research considers the main concepts of the cloud, its architecture, cloud service and deployment models as well as benefits and risks of cloud implementation. Cloud computing benefits are analyzed through the lens of the generic information technology capabilities discussed in the information system value section. The section dedicated towards business process outsourcing aims at introducing the main outsourcing concepts, outlining outsourcing decisions, discussing benefits and risks of the business process outsourcing as well as introducing specifics of outsourcing of the accounting processes. Additionally, this section contains discussion regarding relationship between cloud computing and outsourcing as well as the impact of the cloud computing on outsourcing processes. The main goal of the literature review and background section is to lay theoretical foundations and frameworks for the practical part of the research. The outcome of the literature review is represented by the conceptual framework, which is used during the analysis stage of the research.
The second main objective is dividing the dataset of the organizations into groups with evidently different characteristics based on their outsourcing decisions and create detailed description of each group based on certain criteria, such as improvements in the business processes, cloud adoption, outsourcing patters etc.
The third objective is to analyze the perceived value of the cloud based information systems for each group through the lens of relationship between the use of the cloud based information systems on the perceived improvements in the business processes of the organizations. Sub-goals of the first main objective refer to the following:
If the results of the study show the evidence of the higher improvements in the business processes for the cloud users, the sources of these improvements are to be analyzed and such areas defined, for which the use of the cloud based information systems generate higher perceived improvements compared to non-cloud based information systems;
In case the sources of perceived improvements for cloud users are identified as higher in comparison to non-cloud users, the reasons for better results will be related to the superior capabilities of the cloud based information systems compared to traditional information systems.
The fourth objective of the research is to analyze the relationship between organizations’ outsourcing decisions and perceived improvements in the business processes along with the levels of cloud adoption. The outcome of the fourth objective should be identification of the combined impact of the cloud adoption and outsourcing decisions on perceived improvements and sources of these improvements. Problematic areas, if any, should be outlined and propositions for the further research suggested.
2
Literature review
2.1 Business value of information systems
2.1.1 Concepts and approaches
Information systems (IS) value is generally defined as “the impact of investments in particular information systems assets on the multidimensional performance and capabilities of economic entities at various levels, complemented by the ultimate meaning of performance in the economic environment” (Schryen, 2012). The author further clarifies that the gains or losses an organization achieves through implementation of the information systems derives from the way the information system is exploited. Alternatively, IS business value can be defined as “an outcome is the result of introducing a new IT system, a benefit is what is subsequently derived if the new capability is exploited” (Alshawi, Irani, & Baldwin, 2003). An example of such outcome of an information system can be that a task performed more quickly and the saved time is used to improve the business processes within an organization. Form the angle of performance improvements, information technology business value can be characterized as “organizational performance impacts of IT, including productivity enhancement, profit ability improvement, cost reduction, competitive advantage, inventory reduction, measures of performance” (Melville, Kraemer, & Gurbaxani, 2004).
Thus, as can be seen from the abovementioned definitions, the information systems value is often analyzed from the perspective of the positive impact of the information system on the performance of the business processes of the organization. There are several alternative approaches for identification of the IS value, which consider IS value from different angles as well as various organizational levels.
Most of the previous studies attempt to identify the IS value through the relationship between IT investment and organizational performance. However, inconsistency of the level of analysis (e.g. country, industry, firm, business unit levels) and differences in utilized metrics (accounting-, performance-, economic-, market-based indicators) lead to contradictory findings regarding the impact of the investment into information technology on organization’s productivity. These contradictory findings can range from detecting only
indicators to completely opposite outcomes that indicate considerable investment returns (Mooney, Gurbaxani, & Kraemer, 1996). The inconsistencies in the outcomes of the previously performed studies led to emergence of the concept identified as a “productivity paradox” (Baily & Gordon, 1988). “Productivity paradox” raises the issues of discrepancy between organizations’ levels of investment into information technology and returns of these investments (Mooney et al., 1996).
There are several major reasons of the negative or non-significant impact of the information technology on the business value that were found in earlier research studies (Barua, Kriebel, & Mukhopadhyay, 1995). Among following reasons it is worth to mention measurement problems, lags between IT investments and resulting impacts, redistribution of outputs within the industry and mismanagement (Brynjolfsson, 1993). Thus, one of the major downside of the previous research (Baily & Gordon, 1988) is the focus of the analysis of the information technology impact on the aggregated level that considers the whole organization rather than organization’s certain units, departments or separate processes (Barua et al., 1995).
Such high level of analysis attempts at relating information technology impacts to the overall organization’s performance while ignoring the intermediate processes through which IT impacts arise (Barua et al., 1995). In order to take into account the intermediary processes, the primary impacts of the information technology should be measured “at a lower operational levels in an enterprise, at or near the site where information technology is implemented” allowing in such a way measurement of the “first-order effects” of information technology implementation (Barua et al., 1995). Due to these reasons, process-oriented perspective on the information systems value has become widely adopted by researchers that aimed at demonstrating that the impact of the information systems’ investments on organization’s performance is intermediated by performance of organization’s separate business process (Schryen, 2012).
Some of the most widely used approaches for identification of the information systems’ value through numerous performance indicators include among others following approaches (Schryen, 2012):
− Performance measures; − Process-oriented theories;
− Production-oriented model.
Despite of the fact that each of the abovementioned approach considers information systems value from a slightly different angle, the main commonality among them can be described as strong linkage towards quantifying measurement of the information systems value based on certain performance indicators, which can be represented either by financial or operational indicators. Following paragraphs provide description of each group of approaches and consider their advantages as well as drawbacks for identification of the information systems’ value.
Performance measures
Organization’s performance measures have been widely utilized to analyze the IT / IS business value (Schryen, 2012). Economic measures proved to be most widely used among other performance measures. Such measures include productivity, capacity utilization, product quality, consumer welfare, a set of different profit ratios as well as other market-oriented measures (Schryen, 2012). The following represent some of the most widely used performance measures:
Accounting performance measures: productivity and capacity utilization. Organizational productivity is one of the most widely used accounting performance indicator of evaluation of the information systems value. Despite of the failures of the earlier research in correlating IT investment and increase in firm’s productivity, later studies, especially a study made by Brynjolfsson & Hitt (1996), who analyzed more than 1000 observations, found that computer capital and information systems’ labor significantly increase the output of a firm. It was confirmed that computers contribute significantly to the firm-level output even after the depreciation, possible measurement errors and limitations of the research input data (Brynjolfsson & Hitt, 1996).
The main reasons of such positive correlation in the contrast to the earlier research can be referred to three main factors. First of all, the study was conducted a later period of time compared to earlier research (1987-1991), during which computer
level data was used in the research and finally, usage of the rather large sample of the “Fortune 500” companies (Brynjolfsson & Hitt, 1996).
Other studies also show strong correlation between IT investment and productivity and capacity utilization. Improvements in productivity due to information technology have been detected by applying a production function approach to the analysis of the productivity of IT stock (Hitt & Brynjolfsson, 1996) as well as by evaluating intermediate variable such as capacity utilization and inventory turnover, that represent significant variables in determination of return on assets (ROA) (Barua et al., 1995).
Financial market-based measures: ROA, market share and other financial indicators. Among the financial market-based measures, adopters of the performance-based approach towards determining IS value often utilize ROA, which is calculated as “income from continuing operations before interest expense divided by assets” (Dehning & Stratopoulos, 2002) . Some of the studies that utilized ROA to evaluate IT business value show that companies with IT-enabled strategy and superior IT management skills are more likely to have a sustainable competitive advantage compared to their competitors (Dehning & Stratopoulos, 2002).
Other high level economic performance measures like ROA include, for example, market share, return on sales and value-added as the economic output variables (Barua et al., 1995) or Tobin’s q indicator. Tobin’s q indicator, which is defined as “the capital market value of the firm divided by the replacement value of its assets incorporates a market measure of firm value which is forward-looking, risk-adjusted, and less susceptible to changes in accounting practices”. The results of the research show significant positive correlation between IT expenditures and Tobin’s q (A. S. Bharadwaj, Bharadwaj, & Konsynski, 1999).
Product quality. Attempts have been also made to relate IT investment to the improvements in the quality of the organization’s products. It is suggested that IT facilitates tracking of the changing customer preferences and adjust better to the changing market environment, develop tailor-made products, utilize data mining tools
for identification of the patterns in the data, which as a result leads to the possibility for the companies to create better products for their customers (A. S. Bharadwaj et al., 1999). Other studies also showed the negative correlation between the IT capital, production IT purchases and innovation (e.g. Research and Development (R&D)) as well as IT purchases and inferior quality (Barua et al., 1995).
Consumer welfare. Analysis of the total benefits of consumers based on the consumer surplus approach, showed that IT investment have a significant positive impact on consumer welfare (Hitt & Brynjolfsson, 1996). Thus, it is believed that IT can improve the reliability of the firm’s service, reduce transaction errors, improve performance, develop and manufacture more customized products (A. S. Bharadwaj et al., 1999), which, as a result, leads to better customer service and, hence, improves consumer welfare.
Thus, performance measures have proven to be useful in identification of the business value of the information technology and information systems used in the organizations as they provide simple quantifiable indicators, the use of which allow creating solid business cases for IT investments. Moreover, a relatively high number of the earlier empirical studies with the use of these indicators are available for information technology and business professionals for reference. Despite of this, one significant disadvantage can be identified for the performance measurement approach. This disadvantage refers to the relatively high levels of the performance indicators (often organizational or, at best, business unit levels), which might provide executives with the full picture of the IT investment’s consequences but, at the same time, leave out important details of the concrete benefits information system or IT in general can deliver to specific business processes.
Process-oriented approaches
Process-oriented approach to the information systems value identification aims at eliminating the performance management approach’s problem related to the high level of the analysis. Thus, there has been strong evidence in the literature regarding the necessity to measure IT business value on the process or business unit level rather than on the industry level (Barua et al., 1995; Anandhi S. Bharadwaj, 2000; Dedrick, Gurbaxani, & Kraemer, 2003; Mooney et
information technology on an individual business process and, as a result, defining specific performance measures rather than generalizing the IT impact on the firm level (Mooney et al., 1996). Figure 2 represents one of the examples of the process-oriented model of IT business value.
Figure 1. A process oriented model of IT business value (Mooney et al., 1996)
According to the model presented above, an organization derives business value from IT through the information technology’s impact on organization’s intermediate processes. Therefore, the process view on the IT business value is needed in order to:
− identify the value adding mechanisms of IT;
− develop an approach and set of metrics for measuring the technology's business value; − enhance an understanding of the relationship between IT and organizations (Mooney
et al., 1996).
According to the model suggested above, organization’s business processes are divided into operational processes and management processes that are associated with processing of the information, controlling, coordination, communication and knowledge management. Thus, it is suggested that IT business value should be studied through the lens of the improvements of the management and operational processes enabled by information technology (Mooney et al., 1996).
It should be noted that some confusion in the meaning of the process-oriented approach for defining IS value can be derived from the literature. Thus, some studies suggest the process
theory of business value creation through the information technology, which is focused on the actual IT implementation and IT use process, rather than on considering the value-added impact of the information technology on the organization’s processes. One of such theories is presented in figure 2.
Figure 2. How IT creates business value: process theory (Soh & Markus, 1994)
According to the process theory of IT business value creation, three following IT management related processes are sequentially performed from the point of acquiring and implementing IT assets to the achievement of the organization’s performance improvements:
− IT conversion process; − IT use process;
− Competitive process (Soh & Markus, 1994).
The process theory suggests that IT business value is developed in the following sequence. Organizations spend on IT and due to certain degrees of effectiveness of the IT management process obtain IT assets. Obtained IT assets yield positive IT impacts provided the appropriate and successful IT use. And lastly, positive IT impacts lead to improved organizational performance if they are not negatively affected during competitive process (Soh & Markus, 1994). Thus, the difference of the current approach to the process-oriented approach towards analysis of the information systems value is mainly in their different focus of analysis. Process theory provides the tool for manipulation of the IT management process and shaping in the way that the highest value from IT investment will be delivered in case of the best IT management practices. Thus, this model expands off the boundaries of the IS value identification approaches by providing outline of the IT management process. However, it does not offer any guidelines on how IS value should be measured (e.g. process
level) except for outlining overall organization performance as the measurement scope. Thus, this theory should not be confused with the process-oriented models.
In general, process-oriented approach is a logical outcome of the IS value thinking as it has been evolutionarily developed in order to solve the “productivity paradox” problem, which earlier researchers in the field were facing. As results of the later studies, in which performance indicators were applied to the individual processes in the organizations, showed positive correlations between IT investments and process performance, it can be argued that process-oriented approach proved to be useful in analyzing information systems’ value.
Resource-based view
Another view on the IS value, which is strongly based on the notions of the process-oriented view, refers to the resource-based view (RBV) of the IT assets in the organization. RBV emphasizes heterogeneous firm resources as a basis for competitive advantage (Melville et al., 2004). Evaluation of the IT business value through the lens of the RBV of the firm allows estimation how IT can facilitate an organization to achieve competitive advantage. Resource-based approaches (Anandhi S. Bharadwaj, 2000; Melville et al., 2004) consider IT as the resource that adds value to the organization’s business processes and enhances their performance. In this case the focus of IT business value generation is represented by an organization that invests in and develops IT resources.
According to the RBV, the key IT-based resources are following: 1) IT infrastructure components, 2) human IT resources and 3) intangible IT resources (e.g. developed knowledge assets, customer orientation and IT synergy) (Anandhi S. Bharadwaj, 2000). Thus, IT enables organizations to enhance their customer orientation by providing tools that allow constant monitoring and anticipation of changing customer preferences. From the point of view of the synergy, IT allows resources and information sharing across the whole organizations by removing physical, spatial and temporal limitations to communications. Besides this, flexible IT systems allow easier access and sharing of the information as well as development and production of the products with less additional costs (Anandhi S. Bharadwaj, 2000).
Through the lens of the RBV view IT business value analysis may consist of three domains: 1) focal firm, 2) competitive environment and 3) macro environment (figure 3) (Melville et al., 2004).
Figure 3. Resource-based view of IT business value (Melville et al., 2004)
The focal level firm is comprised by IT resources and complementary organizational resources, which often facilitate and strengthen IT resources by creating synergy with them. IT and complementary resources are applied to the business processes and enhance their performance, which in turn affects the performance of the whole organization. Competitive environment includes the industry characteristics and business processes and IT resources of the focal firm’s trading partners, which affect directly or indirectly organization and functioning of the focal firm’s IT resources. Finally, the macro-environment includes country and non-country factors: e.g. governmental regulations that shape the application and utilization of the focal firm’s IT resources. Such RBV model allows analyzing the IT
resources on different organizational levels and defining the factors affecting IT resources development and utilization (Melville et al., 2004).
In principle, many similarities can be identified between the RBV and process-oriented approaches to analyzing IS value. Thus, both of these approaches consider impact of the information technology on the process level and both apply performance measures to evaluate improvements in organization’s business processes. RBV though can be considered as a more complete approach as it extends the analysis environment beyond the firm or competitive level as in the process-oriented model and considers the macro environment in which the company operates. The value of this extension derives from the fact that by analyzing country or industry environments the organizations are able to adjust their IT needs and choose more suitable IT solutions.
Production-oriented model
The final performance-based approach on IS value analysis refers to the production system framework. Production system framework analyzes the connection between IT (as one component of the input to the business process) and economic performance from the firm-level and industry-firm-level perspectives (figure 4) (Dedrick et al., 2003).
Figure 4. IT and economic performance framework (Dedrick et al., 2003)
larger output for the same amount of input) and, as a result, to better performance of the organization. Complementary management practices (e.g. decentralization of decision-making, business process redesign and total quality management) are critical to the extent of IT investment returns. The industry-level analysis of the IT impact from the point of view of the production systems shows the positive correlation between IT investment and productivity, especially, in the industries, that are utilizing IT extensively (Dedrick et al., 2003).
Thus, it is evident that also the production system approach has a strong connection to the process-oriented view of the IS value as the process plays the central part in the production system. The quality of the outcome of the production system is measured also through performance indicators as in case of the process-oriented and RBV. However, the main disadvantage of the approach is application of only three levels of the performance analysis, the most detailed one of which is the firm level.
Summary: views on information systems value
From the description of the various approaches towards the analysis of the IS value, it can be seen that although some differences exist between the process-oriented, RBV and production systems approaches, the main commonalities such as use of the performance measures / indicators (process, financial and market performance) and process level of analysis suggest the common trend in the performance-based views on the information systems value.
Graphically, synthesis of performance-based approaches for identification of the information systems value can be described as presented in figure 5. General investments and information system related investments serve as the inputs to the business processes, performance of which is measured on the process performance and firm / organizational performance level. Contextual factors, such as industry and country factors affect the environment in which the company operates. Lag effects may further affect the realization of the information systems value from implementation of the information systems.
Figure 5. Synthesis IS business value model (Schryen, 2012)
The main commonalities of the approaches to IS business value that are based on measurement of the firm’s performance indicators, process-oriented approach, resource-based view and production system approach for evaluation of the IS business value, include the following (Schryen, 2012):
− In all abovementioned approaches information systems value is evaluated through the lens of the business performance measures indicators that are applied both on the process or overall organizational performance measures and are represented by market and financial performance indicators.
− As all approaches consider at least the firm level of operation, the impact of IT process performance is dependent on the contextual or environmental factors of a specific firm, industry or country.
− The IS investment can consist of several dimensions: IT expenditures (hardware, software, infrastructure etc.), human resources (e.g. IS training) and IS management capabilities.
− The impact of IT investment needs to take into account the time lag that can account for up to several years.
Thus, performance-based approaches for identification of IS business value concentrate on quantifying and formalizing the business benefits of IT by linking IT investments, which are applied to the organization’s business processes, with economic performance of the process, business unit, firm, industry or country levels. However, despite of the fact that later research shows positive correlation between IT investment and firm’s performance in the form of increase in productivity, such performance indicators have certain limitations. They often assess the processes / business units / firms on a high and abstract level, which does not deliver conclusive results regarding the role of the actual technology in the performance improvements of the business processes.
Besides this, performance measurements do not consider the contextual aspects of the organization and differences between perceptions of the information system’s business value, the degree of which can vary depending on the stakeholders assessing this value. Thus, adoption of the process analysis level from the abovementioned approaches and focusing on the information system’s value as perceived by managers could allow filling in the gap of performance-based analysis approach and obtaining results that take into account human and contextual factors of an organization.
2.1.2 Perceptual view
Number of researches show that perceptions of the organization’s executives are crucial to understand how IT affects firm’s performance (Tallon, Kraemer, & Gurbaxani, 2000). Perceptions and attitudes of CEO’s towards IT directly influence on the extent IT is utilized and developed in the organizations. Attitudes of executives and overall inside climate for IT serve as indicators of how IT is utilized to support the business strategy. However, two biases can be identified in this approach, which refer to the fact that executives might use their own
experience while forming the general perception of IT impacts and that executives are to a large extent exposed to the views of their peers and subordinates regarding performance of IT while making investment decisions. However, executives can still be useful sources for perceptions of IT benefits as they are able to receive various opinions and views from different angles or parties on IT investment and their impact (Tallon et al., 2000). For example, results of a certain empirical research show that organizations that have different goals for IT also found to have different perceptions of IT payoffs (Tallon et al., 2000).
Thus, the IT value may depend on the subjective preferences of actors, that perform the evaluation of IT impact (Sylla & Wen, 2002). An example of such subjective judgment is that a decrease in personnel costs is usually positively evaluated by managers, while staff may consider such a decrease negatively. This argument indicates the necessity to distinguish between performance, which is measured by means of economic indicators, and its potentially different values in terms of the subjective interpretation of different stakeholders (Schryen, 2012). Thus, by analyzing subjective perceptions of IT value it is possible to retrieve “perceived benefits” of IT (Chau, Kuan, & Liang, 2007; Sylla & Wen, 2002).
In the literature there are numerous evaluation methods for tangible benefits of information technology, which rely mostly on the performance and accounting data and are targeted at analyzing IT investment and providing procedures to quantify IT benefits and risks (Sylla & Wen, 2002). However, methods for evaluation of intangible IT benefits “put emphasis on the process of obtaining agreement on objectives through continuous exploration and mutual learning” (Sylla & Wen, 2002). Among such methods it is worth to mention the following: multi-objective, multi-criteria (MOMC), value analysis and critical success factors (CSF) (Sylla & Wen, 2002).
Linking operational characteristics and perceived value
If the value of information systems is strongly related to organization’s operational activities, perceptions of actors that are involved in these activities is crucial (Ragowsky, Stern, & Adams, 2000). Thus, one of the approaches to evaluate perceptions of the mangers regarding information systems value is to link the information systems use and managers’ perceptions of performance of the organization’s operational activities (figure 6). (Ragowsky et al.,
Figure 6. Organizational operational environment and perceived operational performance and IT value (Ragowsky et al., 2000)
Thus, the use of information technology affects organization's primary activities as well as managers' perceptions of the value of that technology (Ragowsky et al., 2000). Each of the primary activities in turn affects organizational performance and management's perceptions of that performance. These perceptions form managers' understanding of the perceived value of the information technology. Operational decisions represent an input to the primary activities, which produces as an output organizational performance.
Thus, this framework allows analyzing the impact of the information technology through the lens of organization’s primary activities as low-level operational decisions affect performance of the whole organization (Barua et al., 1995). Therefore, by analyzing the managerial perceptions of performance of the organization’s activities and linking these perceptions to the use of the certain type of the information system, it could be possible to draw conclusions regarding the value of the information system in case for its certain type managers’ perceptions of performance of the organizations’ activities will be higher.
Information system success factors
Information systems value is strongly related to the benefits that information systems generate for the information intensive processes, which they automate. Thus, dimensions of the perceptual information systems value can be described through the information systems success factors – information system’s performance indicators (DeLone & McLean, 1992) .
These performance indicators are grouped by six dimensions of the information system success and include the following (figure 7) (DeLone & McLean, 1992):
− System quality (quality of the actual system that produces the information);
− Information quality (accuracy, timeliness, meaningfulness of the information etc.); − Use (measurement of the interaction of the information product with recipient);
− User satisfaction (measurement of the interaction of the information product with recipient);
− Individual impact (influence of the information product on management decisions); − Organizational impact (effect of the information product on organizational
performance).
Figure 7. Information system success model (DeLone & McLean, 1992)
Information systems success model has the process nature and should be considered from the perspective of six abovementioned variables as interdependent rather than individual ones (DeLone & McLean, 1992). Thus, system quality and information quality dimensions affect the use and user satisfaction with the information system, which in turn directly shape the individual impact of the information system. Lastly, the individual impact forms an overall organizational impact of the information system.
By selecting information system performance indicators, which can be applied to describe the sources of perceived improvements in the information intensive IT-enabled business processes (DeLone & McLean, 1992), it is possible to define the following indicators:
− Accessibility (enabling easier, faster and more efficient access to the information); − Accuracy (ensuring high quality and fault-free information);
− Usability (ease of use, user-friendly interface and completeness of the functionality of the information system);
− Comparability (ensuring the information produced by the system can be easily contrasted and compared);
− Relevance (ensuring the information provided is relevant and up to date);
− Transparency (ensuring the possibility to review the whole process of data processing).
Thus, based on the perceptual approach towards analysis of the information systems value, perceived value can be identified through two dimensions. The first dimension refers to analyzing perceptions of the managers regarding performance of organization’s operational activities and linking the use of the certain type of the information system to the performance. The second dimension refers to defining the sources of the improvements in operational activities (accessibility, accuracy, usability, comparability, relevance and transparency) and ranking the sources based on their relative importance.
Analysis of the perceptual value of the information systems instead of utilization of the performance based approaches discussed in section 2.1.1 allows taking into account subjective preferences of the organization’s managers, whose opinions and choices may affect organization’s strategy in future.
2.1.3 Value through IT capabilities
Business benefits of the information systems derive through the capabilities of these systems to improve the performance of the business processes by their automation and computerization. The most dominating view on IT capabilities in the literature refers to the resource-based view (Aral & Weill, 2007; Anandhi S. Bharadwaj, 2000; Sunil Mithas, Ramasubbu, & Sambamurthy, 2011; Rai, Pavlou, Im, & Du, 2012; Stoel & Muhanna, 2009).
According to this view, IT capability is defined as organization’s ability to utilize IT-related resources, skills and knowledge to provide desired results for the organization (Stoel & Muhanna, 2009). IT capability can be also considered as organization’s ability to “mobilize and deploy IT-based resources in combination or co-present with other resources and capabilities” (Anandhi S. Bharadwaj, 2000). Thus, organization’s IT capability is formed with IT infrastructure (computer and communication technologies and sharable software and databases), organization’s IT human capital (technical and managerial) and its ability to utilize IT to achieve intangible benefits (customer orientation, synergy and build knowledge assets) (Anandhi S. Bharadwaj, 2000). Together these components create organization-specific resources and, as a result organization-wide IT capability.
According to resource-based view IT capability should be distinguished from IT functionality. IT functionality is considered to be a tool that is designed to automate the business process, while IT capability refers to the use and implementation of IT functionality with other resources to execute the business process (Rai et al., 2012). Thus, the combination between IT assets and organizational resources leads to emergence of organization’s IT-enabled resources (Nevo & Wade, 2010).
Thus, the resource-based view emphasizes the fact that IT assets taken separately do not result in any competitive advantage, as they appear to be the same for any company. The benefit from implementation of the information systems can be truly leveraged only by development of organizational IT capability through building of the excellence in IT expertise and developing efficient IT management process. However, despite of the value of emphasizing the importance of the human factor in utilizing IT assets, the resource-based approach does not consider the actual IT properties that positively affect the business
In the contrast to the resource-based view, IT capabilities can be considered as the effects on the business processes as described in figure 8 (Mooney et al., 1996).
Figure 8. Dimensions of IT business value (Mooney et al., 1996)
Thus, IT can provide automational, informational and transformational effects on a business process. Automational effect of IT refers to IT becoming a substitute for human labor and, as a result, yielding improvements in productivity, labor savings and cost reductions. Informational effects imply IT’s capacity to collect, store, process and disseminate information, which leads to improved decision quality, employee empowerment, decreased us of resources, improved organizational effectiveness. Finally, the transformation effect is expressed with IT’s ability to facilitate and support business process innovation and transformation, which leads to reduced cycle times, improved responsiveness and enhancement of organization’s services or products (Mooney et al., 1996).
Thus, IT is a very powerful tool that can not only support existing processes, but also create new process design options through its generic capabilities that improve coordination and information access across organizational units (Davenport & Short, 1990). The list of eight generic IT capabilities is presented in table 1.
Table 1. IT capabilities and their organizational impacts (Davenport & Short, 1990)
Capability Description
Transactional IT can transform unstructured processes into routinized transactions
Geographical IT can transfer information with rapidity and ease across large distances, making processes independent of geography
Automational IT can replace or reduce human labor in a process
Analytical IT can bring complex analytical methods to bear on a process
Informational IT can bring vast amounts of detailed information into a process
Sequential IT can enable changes in the sequence of tasks in a process, often allowing multiple tasks to be worked on simultaneously
Knowledge management
IT allows the capture and dissemination of knowledge and expertise to improve the process
Tracking IT allows the detailed tracking of task status, inputs, and outputs
Disintermediation IT can be used to connect two parties within a process that would otherwise communicate through an intermediary (internal or external)
IT generic capabilities are not limited to the ones presented in table 1. Each organization can define own IT capabilities that would correspond to the business goals of the organization and characteristics of its business processes (Davenport & Short, 1990). Thus, due to the fact that IT capabilities are directly interdependent with the sources of the information systems value, aligning IT capabilities of an information system type of interest and information system success performance indicators can be utilized as the tool for analyzing perceived value of the information system.
2.2 Cloud based information systems
2.2.1 Concept overview
Cloud computing refers to the information technology service model, where hardware and software services are delivered on-demand to customers across (distributed) IT resources/network in a self-service fashion, independent of the device and location (Marston, Li, Bandyopadhyay, Zhang, & Ghalsasi, 2011; Motahari-Nezhad, Stephenson, & Singhal, 2009). Resources provided by the cloud can be dynamically adjusted allowing for more optimal resource utilization (Vaquero, Rodero-Merino, Caceres, & Lindner, 2009).
Cloud computing emerged as the evolution and technological advancement of the grid and distributed computing, web services, service oriented architecture, utility computing and virtualization (Koehler & Anandasivam, 2010; Motahari-Nezhad et al., 2009; Weiss, 2007). The main value of the cloud computing for businesses derives from offering resources in an economical, scalable and flexible manner, which are affordable and attractive to IT customers and investors (Motahari-Nezhad et al., 2009). It can be argued that promising business benefits of the cloud resulted in raising high expectations. Gartner Research expects cloud computing to be a $150 billion business by 2014, and according to AMI partners, small and medium businesses are expected to spend over $100 billion on cloud computing by 2014 (Marston et al., 2011).
Despite of the impression that might appear while defining the concept of the cloud, the cloud-based information system does not necessarily have to be implemented and hosted by a third-party. It can be also deployed and supported through organization’s internal resources provided that the key principles of the cloud are maintained: resource utilization, virtualized physical resources, architecture abstraction, dynamic scalability of resources, elastic scalability and automated self-provisioning of resources, ubiquity (i.e. device and location independence) and the operational expense model (Bhardwaj, Jain, & Jain, 2010; Marston et al., 2011).
Core technologies and architecture
Cloud computing is based on three core technologies that allowed its evolution to the current state: virtualization, multitenancy and Web services (Marston et al., 2011; Weinhardt et al., 2009).
Virtualization, enabled by two main technologies, such as paravirtualization and hardware-assisted virtualization (Youseff, Butrico, & Silva, 2008), allows providing an emulated computing platform to the users while hiding the platform’s physical characteristics. Such approach enables easy on-demand configurability, maintenance and replicating of the system (Marston et al., 2011).
Multitenancy, which is related to the concept of virtualization, represents the second core technology of the cloud computing. Multitenancy allows sharing a single instance of the application between multiple users rather than duplicating the instance. As a result, the processing overhead and memory usage reduces, which leads to better utilization of the resources (Marston et al., 2011) and cost reduction (Motahari-Nezhad et al., 2009).
Finally, web services as the third major component of the cloud computing, can be described as systems that allow machine-to-machine interaction over the network and, namely, clients and servers that communicate of the Hypertext Transfer Protocol (HTTP). Due to the fact that web services allow standardization of the interfaces between applications, they enable the software client (e.g. a web browser) to easier access server applications (Marston et al., 2011).
Cloud service models
Schematically, architectural layers of cloud computing can be described in the form of service stack. In this model main three layers of the cloud computing architecture are traditionally defined as the application/software layer, platform layer and infrastructure layer (figure 9).
Figure 9. Cloud computing stack (Bhardwaj et al., 2010)
Some models also extend the service stack and include two more service levels into cloud’s architecture – software kernel and firmware / hardware layer (figure 10).
Figure 10. Cloud computing ontology (Youseff et al., 2008)
Cloud computing service models can be grouped into three architectural levels: cloud application, cloud software environment and cloud software infrastructure that is comprised by computational resources, storage and communications. The basis of cloud’s architectural levels are formed by the software kernel that provides software management for the physical cloud’s servers and firmware / hardware layer (Youseff et al., 2008). Each of the service model can provided to the customers as separate service offerings (Bhardwaj et al., 2010). An overview of each cloud’s service model is presented in table 2.
Table 2. Cloud computing service models
Cloud service model Description
Software as a Service (SaaS) Delivery of the application through the medium of the Internet as a service. This type of a service can offer a complete application functionality that ranges from productivity applications (e.g., word processing, spreadsheets, etc.) to programs such as those for Customer Relationship Management (CRM) or Enterprise-Resource Management (ERM) (Sultan, 2011). A SaaS provider typically hosts and manages a given application in their own data center and makes it available to multiple tenants and users over the Web (Bhardwaj et al., 2010).
Platform as a Service (PaaS) Remote delivery of such services as operating systems, databases, middleware, Web servers and other software (Sultan, 2011). Quite often PaaS also represents an application development and deployment platform delivered as a service to developers (Bhardwaj et al., 2010). Service developers are supplied by the cloud service provider with a programming-language-level environment and a set of APIs to facilitate the interaction between the environments and the cloud applications, support the deployment and scalability of the service (Youseff et al., 2008).
Infrastructure as a Service (IaaS)
Remote delivery (through the Internet) of a full computer infrastructure (e.g., virtual computers, servers, storage devices, etc.) (Sultan, 2011) and computational resources enabled by the virtual machines (Youseff et al., 2008). The infrastructure layer provides the necessary resources to the higher-level layers of the cloud based system (Youseff et al., 2008).
Data-Storage as a Service (DaaS)
Remote data storage at remote disks and data access services (Youseff et al., 2008).
Communication as a Service (CaaS)
Provisioning of the service-oriented, configurable, schedulable, predictable and reliable network communication capabilities (Youseff et al., 2008).
Hardware as a Service (HaaS).
Services involving operating, managing and upgrading the physical hardware and switches by the HaaS operator on behalf of its consumers for the life-time of the hardware sublease (Youseff et al., 2008).
Cloud deployment models
Cloud computing can be run based on various deployment models represented by private, community, public or hybrid cloud. More detailed description of each deployment model is presented in table 3.
Table 3. Cloud computing deployment models (Brian et al., 2008; Hoberg, Wollersheim, & Krcmar, 2012)
Deployment model Description
Private cloud The user of the cloud-based solution is a certain organization or user. A private cloud can be run internally or by a third-party provider.
Community cloud Service is used by several members of a certain group and may be offered by several internal or external providers.
Public cloud Service is available to the public and generally provided by a single provider.
Hybrid cloud Combination of various deployment models and forms (e.g. sensitive data is provided in the private cloud, while publicly available data in the public cloud).
An illustration of the cloud computing deployment models is provided in the figure 11.
Figure 11. Illustration of cloud computing models (Géczy, Izumi, & Hasida, 2012)
According to figure 11, the critical resources and processes in the organization tend to be implemented as the private cloud while non-critical are often moved to the public cloud. It is worth to mention that implementation of the private clouds are more typical for large organizations that aim at reducing underutilization of the processing power. On the other hand, medium-sized and smaller companies are more prone to use the public clouds (Motahari-Nezhad et al., 2009).
2.2.2 Benefits of cloud computing
Cloud computing benefits
Implementation of the cloud based information systems is believed to result in significant business benefits due to cloud computing’s superior capabilities in comparison with traditional information systems (Aljabre, 2012; Armbrust et al., 2010; Leimeister, Böhm,
Riedl, & Krcmar, 2010; Marston et al., 2011; Mohammed, Altmann, & Hwang, 2009). Therefore, for the purpose of current research the benefits of the cloud computing are analyzed through the lens of relevant Devanport’s generic IT capabilities discussed in section 2.1.2.2. General business benefits are presented before information system’s capabilities.
Business benefits
Cloud technology is paid incrementally, which leads to the possibility for the organizations to save money (Bhardwaj et al., 2010). Cloud computing also brings cost allocation flexibility for organizations that aim at moving capital expenditures into operational expenditures. Organization’s costs are reduced due to improvement of the operational efficiency and, as a result allow more rapid deployment of new services or products (Bhardwaj et al., 2010).
Cost savings for the organizations derive through lower cost computers for users and no heavy investments in IT infrastructure, hardware or software licensees of expensive large-scale information systems (Aljabre, 2012; Marston et al., 2011). Lower required investment in IT lead to lower barriers to entry for newly established organizations into certain business areas (Marston et al., 2011).
Automational capability
Automational and transactional capabilities of the information systems grouped as the automational capability allows automation of the routine business processes through implementation of the IT with the aim of increasing processes’ performance efficiency. Routine processes are characterized with the lower extent of expertise and special knowledge required to perform the processes, in such a way making processes more standardizable. In turn, the more standardizable and modularizable the processes are, the easier IT can be applied to automate the business processes and, as a result, generate business value.
By considering the benefits of the cloud based information systems through the lens of the automational capability, it can be argued that principles of reusable infrastructure and modularity, which lay in the basis of cloud computing, allow more efficient automation of the standardizable routine processes compared to traditional computing methods (Iyer &
easier and smoother software upgrade and update process enabled by principles of decoupling and separation of the business service from the infrastructure needed to run it (i.e. implementation of the virtualization techniques) (Bhardwaj et al., 2010). Thus, automation of the server updates and handling of the computing challenges by the third-party can allow organizations to ensure the reliability and accessibility of the service (Bhardwaj et al., 2010). Scalability and high reliability are also considered to be important requirements for the cloud based information systems and, as a result, are major components in the cloud system’s architecture (Klems, Nimis, & Tai, 2009).
More efficient automation of the business processes is also enabled through better integrating capabilities of cloud computing due to the fact that cloud’s architectural principles enable better compatibility between applications and operating systems (Aljabre, 2012). As a result, the business processes of the organization are not only being automated within a certain business unit, but also are able to share the data and functionality with information systems from other units.
Cloud based systems are able to decrease he number of employees to operate IT infrastructure and, as a result, lead to increase of profits while decreasing the costs (Aljabre, 2012). The main reason of decrease in costs is related to decrease in number of the employees required to operate IT infrastructure, savings related to less purchases of IT equipment and lower real estate renting costs due to less space required for IT equipment (Aljabre, 2012). Besides this, cloud computing is based on principles of reusable infrastructure and modularity (Iyer & Henderson, 2010) that facilitate automation of the routing processes.
Therefore, the automational capability of the cloud based information systems is strengthened with the architectural specifics of cloud computing and, as a result, assumingly leads to the improvements in usability and relevance of the data used by the business processes.
Information processing capability
The higher the information intensive of the service activity, the easier it is to use the information technology to perform this activity at a time and location that is more efficient and results in higher quality (Apte & Mason, 1995). Cloud based information systems
processing capabilities due to the elastic nature of the cloud computing infrastructure, which allows rapid allocation and de-allocation of the massively scalable resources to business services on a demand basis (Bhardwaj et al., 2010) and reduction of the time to process “computer-intensive or data-intensive jobs” (Aljabre, 2012). Such rapid elasticity capability of the cloud based information systems allows organizations to rapidly scale up service usage and, as a result, mirror information processing demands of organization (Iyer & Henderson, 2010), providing organizations with additional flexibility and scalability capabilities.
Besides scalability of the information processing power, flexibility of the cloud computing also arises from the possibility of the organizations to choose multiple vendors that provide reliable and scalable business services, development environments and infrastructure with no long term contracts (Bhardwaj et al., 2010). In such a way organizations are able to minimize the risks of provider lock-in and achieve service flexibility and scalability, which are defined among major cloud computing benefits (Carroll, Merwe, & Kotzé, 2011) (figure 12).
Figure 12. Cloud computing benefits (Carroll et al., 2011)
Information processing capability of the cloud computing is also strengthened with cloud’s architecture. Cloud’s controlled interface delivered through Application Programming Interfaces (APIs) makes applications more accessible by other applications and systems and,
as a result allows the possibility for certain business units utilize analytical tools and access data of other units or external organizations (Iyer & Henderson, 2010). Organization-wide integration and centralized storage of the data in cloud computing systems is enabled through the sourcing interdependence, which allows sharing the information that is stored in the same format between different information systems (Iyer & Henderson, 2010). Due to powerful specialized data center servers and centralized data storage organizations are able to store more data in the cloud than on private computer systems (Bhardwaj et al., 2010). This enhances knowledge management capabilities of the cloud and, as a result, allows organization to utilize data more efficiently for analysis and decision-making purposes.
Through enhances in information processing, analytical and knowledge management capabilities, cloud computing enables development of virtual business environments, that can be defined as “a suite of integrated applications (processes) and tools that support specific, major business capabilities or needs” (Iyer & Henderson, 2010). Virtual business environments provide decision makers with integrated and seamless access to all the capabilities needed to analyze and execute business decisions.
Altogether, controlled interfaces, sourcing interdependence, centralized data storage and possibility to create knowledge sharing virtual business environments, cloud based information systems provides more possibilities for cross-organizational analysis and, as a result, improving information processing, analytical and knowledge management capabilities compared to traditional systems. Cloud benefits in terms of the information processing capabilities can be assumed to positively affect improvements in the areas of accuracy, comparability and understandability of the data utilized by the business processes in organizations.
Geographical capability
Geographical capability of the information technology allows transferring the information with rapidity and ease across large distances, making processes independent of geography (Davenport & Short, 1990). Geographical capability is interdependent with sequential and disintermediation capabilities of the information technology, which allow easier and shared access to the organizational data despite of the location or number of users.